class_docstr: implementation of HighRes3DNet:
    Li et al., "On the compactness, efficiency, and representation of 3D
    convolutional networks: Brain parcellation as a pretext task", IPMI '17
class_docstr_tok: ["implementation","of","HighRes3DNet",":","Li","et","al.",",","``","On","the","compactness",",","efficiency",",","and","representation","of","3D","convolutional","networks",":","Brain","parcellation","as","a","pretext","task","''",",","IPMI","'17"]
code: def _print(self, list_of_layers):
      for op, _ in list_of_layers:
          print(op)
  
file_path: NiftyNet/niftynet/contrib/csv_reader/class_seg_finnet.py
imports: from __future__ import absolute_import, print_function
  from six.moves import range
  from niftynet.layer import layer_util
  from niftynet.layer.activation import ActiLayer
  from niftynet.layer.base_layer import TrainableLayer
  from niftynet.layer.bn import BNLayer
  from niftynet.layer.convolution import ConvLayer, ConvolutionalLayer
  from niftynet.layer.dilatedcontext import DilatedTensor
  from niftynet.layer.elementwise import ElementwiseLayer
  from niftynet.network.base_net import BaseNet
  from niftynet.layer.layer_util import infer_spatial_rank
  from niftynet.layer.fully_connected import FullyConnectedLayer
  import tensorflow
label_desc: Use image node_id 3 for calling the ClassSegFinnet obj's underlying member method code with example usage: obj._print(list_of_layers) without return types